Determination of Hydrological Flood Hazard Thresholds and Flood Frequency Analysis: Case Study of Nokoue Lake Watershed

With the impacts of climate change, floods have become increasingly frequent in recent years. Estimating flood hazard thresholds and peak floodwater levels based on flood frequency analysis is crucial for anticipating and preparing for potential flooding events. This study aims to estimate flood hazard thresholds, flood occurrence probabilities, and the return periods of peak floodwater levels in the Nokoue lake watershed in Benin. To achieve this, the standardized water level index, also known as the Flood hazard Index, was calculated to estimate flood hazard thresholds. The three best probability distribution models, Gumbel, Generalized Extreme Value (GEV), and Generalized Pareto (GPA), were selected to project future floodwater levels using annual maximum daily water level data for extreme floods from 1997 to 2022, obtained from a water gauge site at Nokoue lake. Three goodness-of-fit tests were applied to identify the best-fitting probability distribution model: a Taylor diagram (three-dimensional analysis), a cumulative probability density diagram based on the root-mean-square error (RMSE), and an L-moment diagram (two-dimensional analysis). The Flood hazard Index values ranged from −1.10 to +3.40, with 77.78% showing positive indices and 22.22% showing negative indices. The flood hazard thresholds were classified in ascending order of index values: limited hazards, moderate hazards, significant hazards, and critical hazards. The analysis results indicate that the flood hazard thresholds are defined as follows: below 3.94 m for limited hazards, from 3.94 m up to 4.04 m for moderate hazards, from 4.04 m to 4.14 m for significant hazards, and above 4.14 m for critical hazards. The distribution model analysis showed that the Gumbel distribution best fits the Nokoue lake watershed, with an RMSE of 0.0724, compared to 0.0754 and 0.0761 for the GEV and GPA models, respectively. The annual maximum daily water levels for various non-exhaustive return periods, 2, 3, 5, 10, 25, 50, and 100 years, were estimated and compared. The return period for the highest recorded annual maximum daily water levels (4.4 m/day) in the Nokoue lake watershed were calculated to be 12, 15, and 15 years using the Gumbel, GEV, and GPA models, respectively. Quantile analysis revealed that the Gumbel distribution produced overestimated results compared to the GEV and GPA models for return periods exceeding 10 years. Exceptional and very exceptional hydrological events have return periods of 100 and 150 years, corresponding to peak flow levels of 4.95 m and 5.05 m respectively. Finally, the results of this study will be invaluable for flood hazard managers in monitoring flood alerts and for water resource engineers in determining dimensions for designing flood control structures such as spillways, dams, and bridges, thereby improving the management of recurrent flooding events.